Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology
Wu, Sean L., Sánchez, Héctor M., Henry, John M., Citron, Daniel T., Zhang, Qian, Compton, Kelly, Liang, Biyonka, Verma, Amit, Cummings, Derek A.T., Le Menach, Arnaud, Scott, Thomas W., Wilson, Anne L., Lindsay, Steven W., Moyes, Catherine L., Hancock, Penny A., Russell, Tanya L., Burkot, Thomas R., Marshall, John M., Kiware, Samson, Reiner, Robert C., and Smith, David L. (2020) Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology. PLoS Computational Biology, 16 (4). e1007446.
|
PDF (Published Version)
- Published Version
Available under License Creative Commons Attribution. Download (3MB) | Preview |
Abstract
Mosquitoes are important vectors for pathogens that infect humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we re-examine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for individual-based simulation models called MBITES (Mosquito Bout-based and Individual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While mosquito infection and pathogen development are one possible part of a mosquito’s state, that is not our main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations’ capacity to transmit pathogens.
Item ID: | 64073 |
---|---|
Item Type: | Article (Research - C1) |
ISSN: | 1553-7358 |
Copyright Information: | © 2020 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Funders: | Bill and Melinda Gates Foundation (BMGF), US National Institutes of Allergies and Infectious Diseases (NIAID) |
Projects and Grants: | BMGF OPP1110495, NIAID U19-A1089673 |
Date Deposited: | 30 Aug 2020 21:09 |
FoR Codes: | 42 HEALTH SCIENCES > 4202 Epidemiology > 420203 Environmental epidemiology @ 100% |
SEO Codes: | 92 HEALTH > 9205 Specific Population Health (excl. Indigenous Health) > 920599 Specific Population Health (excl. Indigenous Health) not elsewhere classified @ 100% |
Downloads: |
Total: 713 Last 12 Months: 8 |
More Statistics |